Matches in SemOpenAlex for { <https://semopenalex.org/work/W848261778> ?p ?o ?g. }
Showing items 1 to 63 of
63
with 100 items per page.
- W848261778 endingPage "830" @default.
- W848261778 startingPage "817" @default.
- W848261778 abstract "The world of pharmacology is becoming increasingly dependent on the advances in the fields of genomics and proteomics. The –omics sciences bring about the challenge of how to deal with the large amounts of complex data they generate from an intelligent data analysis perspective. In this chapter, the authors focus on the analysis of a specific type of proteins, the G protein-coupled receptors, which are the target for over 15% of current drugs. They describe a kernel method of the manifold learning family for the analysis of protein amino acid symbolic sequences. This method sheds light on the structure of protein subfamilies, while providing an intuitive visualization of such structure." @default.
- W848261778 created "2016-06-24" @default.
- W848261778 creator A5022815896 @default.
- W848261778 creator A5028083196 @default.
- W848261778 creator A5071469507 @default.
- W848261778 creator A5088909083 @default.
- W848261778 creator A5089054159 @default.
- W848261778 date "2013-04-01" @default.
- W848261778 modified "2023-09-26" @default.
- W848261778 title "Kernel Generative Topographic Mapping of Protein Sequences" @default.
- W848261778 cites W1510073064 @default.
- W848261778 cites W1542652324 @default.
- W848261778 cites W1587559447 @default.
- W848261778 cites W1603274157 @default.
- W848261778 cites W1965648329 @default.
- W848261778 cites W1968682237 @default.
- W848261778 cites W1991426267 @default.
- W848261778 cites W1995089537 @default.
- W848261778 cites W2021123210 @default.
- W848261778 cites W2023343746 @default.
- W848261778 cites W2057791956 @default.
- W848261778 cites W2080875376 @default.
- W848261778 cites W2087407051 @default.
- W848261778 cites W2099930159 @default.
- W848261778 cites W2107636931 @default.
- W848261778 cites W2111051539 @default.
- W848261778 cites W2120166371 @default.
- W848261778 cites W4244065306 @default.
- W848261778 cites W4245176872 @default.
- W848261778 cites W4251828057 @default.
- W848261778 doi "https://doi.org/10.4018/978-1-4666-3604-0.ch044" @default.
- W848261778 hasPublicationYear "2013" @default.
- W848261778 type Work @default.
- W848261778 sameAs 848261778 @default.
- W848261778 citedByCount "0" @default.
- W848261778 crossrefType "book-chapter" @default.
- W848261778 hasAuthorship W848261778A5022815896 @default.
- W848261778 hasAuthorship W848261778A5028083196 @default.
- W848261778 hasAuthorship W848261778A5071469507 @default.
- W848261778 hasAuthorship W848261778A5088909083 @default.
- W848261778 hasAuthorship W848261778A5089054159 @default.
- W848261778 hasConcept C114614502 @default.
- W848261778 hasConcept C154945302 @default.
- W848261778 hasConcept C33923547 @default.
- W848261778 hasConcept C39890363 @default.
- W848261778 hasConcept C41008148 @default.
- W848261778 hasConcept C74193536 @default.
- W848261778 hasConceptScore W848261778C114614502 @default.
- W848261778 hasConceptScore W848261778C154945302 @default.
- W848261778 hasConceptScore W848261778C33923547 @default.
- W848261778 hasConceptScore W848261778C39890363 @default.
- W848261778 hasConceptScore W848261778C41008148 @default.
- W848261778 hasConceptScore W848261778C74193536 @default.
- W848261778 hasLocation W8482617781 @default.
- W848261778 hasOpenAccess W848261778 @default.
- W848261778 hasPrimaryLocation W8482617781 @default.
- W848261778 hasRelatedWork W2494243223 @default.
- W848261778 isParatext "false" @default.
- W848261778 isRetracted "false" @default.
- W848261778 magId "848261778" @default.
- W848261778 workType "book-chapter" @default.